Centering on the main line of intelligent development of civil aviation, carrying out the application and product development of airport digital twin technology is a key link to promote the integrated development of digital economy and real economy. In the airport flight scheduling work, under normal circumstances, the flight planning time (arrival time, departure time) will be planned, without the need for AOC transfer. However, when special circumstances occur, AOC will select some flights in the next day's flight schedule to adjust their arrival time or departure time to the rest of the time according to demand. However, manual timing is time-consuming and requires a certain amount of experience, so an automatic timing algorithm that can meet the actual needs has an urgent need to improve the efficiency of AOC.
{"title":"Timing algorithm design based on digital twin airport","authors":"Wei Wang, Hairui Song, Liping Yan, Senping Song","doi":"10.1117/12.3031969","DOIUrl":"https://doi.org/10.1117/12.3031969","url":null,"abstract":"Centering on the main line of intelligent development of civil aviation, carrying out the application and product development of airport digital twin technology is a key link to promote the integrated development of digital economy and real economy. In the airport flight scheduling work, under normal circumstances, the flight planning time (arrival time, departure time) will be planned, without the need for AOC transfer. However, when special circumstances occur, AOC will select some flights in the next day's flight schedule to adjust their arrival time or departure time to the rest of the time according to demand. However, manual timing is time-consuming and requires a certain amount of experience, so an automatic timing algorithm that can meet the actual needs has an urgent need to improve the efficiency of AOC.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 11","pages":"131710Q - 131710Q-7"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the advancement of satellite communication technology and space launch technology, low earth orbit (LEO) satellites have become the best choice to overcome geographical limitations and achieve global communication. In order to achieve efficient performance in the large-scale LEO constellation network, a routing algorithm adapted to satellite network is necessary. A routing algorithm based on on-demand routing is proposed to address the issues of high network overhead and difficult routing in the large-scale LEO constellation. "Maximum routing restriction area" is defined based on the satellite network structure to reduce the routing overhead in the large-scale constellation network and improve network performance. The simulation results show that this algorithm has better network performance in the large-scale constellation network compared to the other on-demand routing algorithms.
{"title":"A distributed on-demand routing algorithm for large-scale low Earth orbit constellation","authors":"Hefei Hu, siyan lv, Jun He, Simin Feng","doi":"10.1117/12.3031951","DOIUrl":"https://doi.org/10.1117/12.3031951","url":null,"abstract":"With the advancement of satellite communication technology and space launch technology, low earth orbit (LEO) satellites have become the best choice to overcome geographical limitations and achieve global communication. In order to achieve efficient performance in the large-scale LEO constellation network, a routing algorithm adapted to satellite network is necessary. A routing algorithm based on on-demand routing is proposed to address the issues of high network overhead and difficult routing in the large-scale LEO constellation. \"Maximum routing restriction area\" is defined based on the satellite network structure to reduce the routing overhead in the large-scale constellation network and improve network performance. The simulation results show that this algorithm has better network performance in the large-scale constellation network compared to the other on-demand routing algorithms.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 2","pages":"131710C - 131710C-7"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To improve radar signal detection accuracy of traditional methods under low SNR, a detection method based on stacked auto-encoder (SAE) and time-frequency domain features is proposed. The time-domain features, frequency-domain features and joint time-frequency domain features of signal are extracted by SAE to obtain the representative features of radar signal. The extracted features are input into support vector data description (SVDD) for open-set judgment to distinguish radar signal from background signal. Simulation results show that the accuracy and robustness of object detection are improved and the performance of object detection algorithms in complex environments is improved by integrating time-domain features and frequency-domain features information from the target background into detection decisions. It has practical significance for improving the detection accuracy of radar signal detection under low SNR.
{"title":"Radar signal detection under low SNR using stacked auto-encoder and time-frequency domain features","authors":"Yuan Huang, Tao Liu, Ke Li","doi":"10.1117/12.3032046","DOIUrl":"https://doi.org/10.1117/12.3032046","url":null,"abstract":"To improve radar signal detection accuracy of traditional methods under low SNR, a detection method based on stacked auto-encoder (SAE) and time-frequency domain features is proposed. The time-domain features, frequency-domain features and joint time-frequency domain features of signal are extracted by SAE to obtain the representative features of radar signal. The extracted features are input into support vector data description (SVDD) for open-set judgment to distinguish radar signal from background signal. Simulation results show that the accuracy and robustness of object detection are improved and the performance of object detection algorithms in complex environments is improved by integrating time-domain features and frequency-domain features information from the target background into detection decisions. It has practical significance for improving the detection accuracy of radar signal detection under low SNR.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 9","pages":"131711A - 131711A-6"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141370216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the realm of cloud computing, long sequence prediction of workloads plays a pivotal role, crucial for optimizing resource allocation and enhancing system performance. However, current research of long-sequence workload forecasting faces a series of challenges, mainly due to the high randomness and instability characteristics of long workload sequences, making it difficult for traditional machine learning methods to provide accurate results. Therefore, we designed a novel approach for long sequence forecasting, thoroughly considering the latent characteristics of cloud workload sequences. Initially, we employ convolution kernels of varying sizes to perform multiscale sequence decomposition, better capturing contextual information and periodic features in long sequence. Furthermore, through fast Fourier transformation, we convert one-dimensional sequences into two-dimensional space, leveraging dilated convolutions to extract effective features within the intra-period and inter-period variations. Ultimately, we introduce an attention mechanism, effectively integrating the intra-period and inter-period variation features into the proposed model. Our method has undergone comprehensive evaluation on publicly available datasets from Google, Alibaba, and Microsoft. Experimental results demonstrate superior accuracy and robustness of our model across various workload types, showcasing its excellent adaptability to dynamic and complex workload scenarios.
{"title":"Exploiting sequence characteristics for long-term workload prediction in cloud data centers","authors":"Zongxiao Chen, Weijian Zheng, Yusong Zhou, Huile Wang, Weiping Zheng","doi":"10.1117/12.3032105","DOIUrl":"https://doi.org/10.1117/12.3032105","url":null,"abstract":"In the realm of cloud computing, long sequence prediction of workloads plays a pivotal role, crucial for optimizing resource allocation and enhancing system performance. However, current research of long-sequence workload forecasting faces a series of challenges, mainly due to the high randomness and instability characteristics of long workload sequences, making it difficult for traditional machine learning methods to provide accurate results. Therefore, we designed a novel approach for long sequence forecasting, thoroughly considering the latent characteristics of cloud workload sequences. Initially, we employ convolution kernels of varying sizes to perform multiscale sequence decomposition, better capturing contextual information and periodic features in long sequence. Furthermore, through fast Fourier transformation, we convert one-dimensional sequences into two-dimensional space, leveraging dilated convolutions to extract effective features within the intra-period and inter-period variations. Ultimately, we introduce an attention mechanism, effectively integrating the intra-period and inter-period variation features into the proposed model. Our method has undergone comprehensive evaluation on publicly available datasets from Google, Alibaba, and Microsoft. Experimental results demonstrate superior accuracy and robustness of our model across various workload types, showcasing its excellent adaptability to dynamic and complex workload scenarios.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 4","pages":"131710D - 131710D-7"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A set S⊆V(G) in graph G is a [j, k]-set if it satisfies that G[S] is a subgraph of G and each vertex v∈V(G)∖S, has j≤∣N(v)∩S∣≤k, wherein j and k are nonnegative integers. In this paper, we focus on the situation of j=1, k=2, that is, [1,2]-set of graph G. We mainly study the situation of γ(T)-set and γ[1,2](T)-set in tree, and analyse a particular tree called spider. Then discuss with two different algorithm to calculate the [1,2]-domination number γ[1,2](T) in tree. Finally, compare and analyze the calculation results.
如果满足 G[S] 是 G 的子图且每个顶点 v∈V(G)∖S 有 j≤∣N(v)∩S∣≤k，其中 j 和 k 为非负整数，则图 G 中的一个集合 S⊆V(G) 是 [j, k]-set 。本文主要研究树中 γ(T)-set 和 γ[1,2](T)-set 的情况，并分析了一种称为 spider 的特殊树。然后讨论计算树中[1,2]-域数γ[1,2](T)的两种不同算法。最后，比较并分析计算结果。
{"title":"The [1,2]-set properties and algorithm analysis of tree","authors":"Chao Zhang, Tao Chen","doi":"10.1117/12.3031908","DOIUrl":"https://doi.org/10.1117/12.3031908","url":null,"abstract":"A set S⊆V(G) in graph G is a [j, k]-set if it satisfies that G[S] is a subgraph of G and each vertex v∈V(G)∖S, has j≤∣N(v)∩S∣≤k, wherein j and k are nonnegative integers. In this paper, we focus on the situation of j=1, k=2, that is, [1,2]-set of graph G. We mainly study the situation of γ(T)-set and γ[1,2](T)-set in tree, and analyse a particular tree called spider. Then discuss with two different algorithm to calculate the [1,2]-domination number γ[1,2](T) in tree. Finally, compare and analyze the calculation results.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 42","pages":"131710O - 131710O-4"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141370720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pythagorean fuzzy sets (PFS) as a generation of Fuzzy sets has the greater representation space in handling uncertain information, which is applied to many fields. Distance between PFS which can measure the difference or discrepancy grade. Obviously, the distance between (1,0) and (0,1) is different from that between (0,0) and (0,1). However, some distance measure methods violate this result. To address above problem, the paper proposes a new distance measure based on geometric compression. In FPS, the sum of squares of membership, non-membership and hesitant is 1. In new method, membership, non-membership and hesitant information are regarded as x, y, z-axis to establish a space rectangular coordinate system. Based on the unit circle, the membership, non-membership and hesitant information are compressed to get the deformable ellipsoid. For hesitant information, it can be regarded to contain membership and non-membership information from the view of Dempster-Shafer evidence theory. What’s more, new distance measure not only satisfies the axiomatic definition of distance measure but also has nonlinear characteristics. In addition, the advantages of new method are indicated by comparing with other distance measure methods. Finally, the paper apply new method in the Multiattribute decision making problem, which provides a promising solution for addressing decision-making problems.
{"title":"Distance measure based on geometric compression of Pythagorean fuzzy sets","authors":"Haoxin Gai, Xiaozhuan Gao","doi":"10.1117/12.3032001","DOIUrl":"https://doi.org/10.1117/12.3032001","url":null,"abstract":"Pythagorean fuzzy sets (PFS) as a generation of Fuzzy sets has the greater representation space in handling uncertain information, which is applied to many fields. Distance between PFS which can measure the difference or discrepancy grade. Obviously, the distance between (1,0) and (0,1) is different from that between (0,0) and (0,1). However, some distance measure methods violate this result. To address above problem, the paper proposes a new distance measure based on geometric compression. In FPS, the sum of squares of membership, non-membership and hesitant is 1. In new method, membership, non-membership and hesitant information are regarded as x, y, z-axis to establish a space rectangular coordinate system. Based on the unit circle, the membership, non-membership and hesitant information are compressed to get the deformable ellipsoid. For hesitant information, it can be regarded to contain membership and non-membership information from the view of Dempster-Shafer evidence theory. What’s more, new distance measure not only satisfies the axiomatic definition of distance measure but also has nonlinear characteristics. In addition, the advantages of new method are indicated by comparing with other distance measure methods. Finally, the paper apply new method in the Multiattribute decision making problem, which provides a promising solution for addressing decision-making problems.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 34","pages":"1317114 - 1317114-6"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141370727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aiming at the problems of traditional A* algorithm with many inflection points, long paths and low efficiency, this paper proposes a multi-domain A* algorithm. Firstly, it improves the obstacle search method and node passable discrimination method, and optimizes the path generation process of the algorithm. Then study the effect of different neighborhood search matrices on the algorithm's path nodes and path length, and select the optimal neighborhood search matrix. Since the improved A* algorithm has a larger neighborhood and more choices than the traditional A* algorithm, compared with the traditional A* algorithm the path length is reduced by 7.2%, the path nodes are reduced by 47.4%, and the search time is reduced by 82.6%, in addition, the path of the improved A* algorithm is smoother.
{"title":"Multidomain A* algorithm research","authors":"Peitao Guo, Zhihong Xi, Guanhua Wang, Fenghao Zheng, Kexin Zhang","doi":"10.1117/12.3031937","DOIUrl":"https://doi.org/10.1117/12.3031937","url":null,"abstract":"Aiming at the problems of traditional A* algorithm with many inflection points, long paths and low efficiency, this paper proposes a multi-domain A* algorithm. Firstly, it improves the obstacle search method and node passable discrimination method, and optimizes the path generation process of the algorithm. Then study the effect of different neighborhood search matrices on the algorithm's path nodes and path length, and select the optimal neighborhood search matrix. Since the improved A* algorithm has a larger neighborhood and more choices than the traditional A* algorithm, compared with the traditional A* algorithm the path length is reduced by 7.2%, the path nodes are reduced by 47.4%, and the search time is reduced by 82.6%, in addition, the path of the improved A* algorithm is smoother.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 7","pages":"131710N - 131710N-5"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, the combination of a service function chain (SFC) with network function virtualization (NFV) and softwaredefined networking (SDN) has provided customers with flexible and efficient services. The emergence of multi-access edge computing (MEC) further enhances the level of service customization. However, achieving joint optimization of virtual network function (VNF) deployment and flow allocation in resource-constrained scenarios while meeting the diverse requirements of 5G verticals is challenging. Current research rarely addresses dedicated service provisioning for edge servers and considers the additional instantiation overhead introduced by adjusting cloud server parameters. In fact, this is a non-negligible issue during SFC deployment in 5G-MEC scenarios. Based on the above considerations, this paper constructs a joint SFC deployment problem for edge-cloud networks with the goal of maximizing network utility. We first propose a univariate modeling method based on meta-links that effectively avoids the variable coupling problem in traditional multivariate modeling approaches and reduce the problem size by at least half. Subsequently, to solve the NPhard integer nonlinear problem (INLP), we propose a distributed computing architecture named SP-ADMM, which improves the speed and quality of SFC deployment in large-scale scenarios via convex combinatorial formulations and a Viterbi-based heuristic algorithm (PAC-GREP). Finally, we experimentally verify the convergence and approximation of the algorithms. Our solution demonstrates advantages in terms of network utility and convergence speed under the same network resources, increasing service capacity by at least 39%.
{"title":"SP-ADMM: a distributed optimization method of SFC placement for 5G-MEC networks","authors":"Zhibo Zhang, Hui-qiang Wang, Shuangyue Niu, Hongwu Lv","doi":"10.1117/12.3031950","DOIUrl":"https://doi.org/10.1117/12.3031950","url":null,"abstract":"Recently, the combination of a service function chain (SFC) with network function virtualization (NFV) and softwaredefined networking (SDN) has provided customers with flexible and efficient services. The emergence of multi-access edge computing (MEC) further enhances the level of service customization. However, achieving joint optimization of virtual network function (VNF) deployment and flow allocation in resource-constrained scenarios while meeting the diverse requirements of 5G verticals is challenging. Current research rarely addresses dedicated service provisioning for edge servers and considers the additional instantiation overhead introduced by adjusting cloud server parameters. In fact, this is a non-negligible issue during SFC deployment in 5G-MEC scenarios. Based on the above considerations, this paper constructs a joint SFC deployment problem for edge-cloud networks with the goal of maximizing network utility. We first propose a univariate modeling method based on meta-links that effectively avoids the variable coupling problem in traditional multivariate modeling approaches and reduce the problem size by at least half. Subsequently, to solve the NPhard integer nonlinear problem (INLP), we propose a distributed computing architecture named SP-ADMM, which improves the speed and quality of SFC deployment in large-scale scenarios via convex combinatorial formulations and a Viterbi-based heuristic algorithm (PAC-GREP). Finally, we experimentally verify the convergence and approximation of the algorithms. Our solution demonstrates advantages in terms of network utility and convergence speed under the same network resources, increasing service capacity by at least 39%.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 29","pages":"131711R - 131711R-10"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nan Lin, Yongpeng Niu, Kaipeng Tang, Hao Duan, Yingkang Han
Targeting the challenge where the substantial labeling expense of ECG data contributes to the present dearth of labeled ECG datasets and the subpar segmentation precision of contemporary models, this paper proposes an ECG segmentation model NGA-Net,the model is based on RRU-Net, with the addition of the ASPNL module and the improved Ghost module, in which the improved Ghost module is designed to generate an increased quantity of feature maps using a reduced parameter set, thereby boosting computational efficiency; The ASPNL module can capture ECG signal features from multiple scales to enhance the efficiency of feature extraction. Experimental evidence indicates that the ECG segmentation model, NGA-Net, introduced in this research, exhibits superior performance in comparison to other methodologies when tested on the publicly available LUDB dataset, which demonstrates the effectiveness of NGANet.In this research, we adopt a semi-supervised learning strategy for training the NGA-Net in scenarios with small sample sizes, leveraging data augmentation and consistency training methodologies. The experimental findings corroborate the effectiveness of semi-supervised learning in augmenting the performance of deep learning models.
{"title":"NGA-Net: an ECG waveform segmentation algorithm based on semisupervised learning","authors":"Nan Lin, Yongpeng Niu, Kaipeng Tang, Hao Duan, Yingkang Han","doi":"10.1117/12.3031916","DOIUrl":"https://doi.org/10.1117/12.3031916","url":null,"abstract":"Targeting the challenge where the substantial labeling expense of ECG data contributes to the present dearth of labeled ECG datasets and the subpar segmentation precision of contemporary models, this paper proposes an ECG segmentation model NGA-Net,the model is based on RRU-Net, with the addition of the ASPNL module and the improved Ghost module, in which the improved Ghost module is designed to generate an increased quantity of feature maps using a reduced parameter set, thereby boosting computational efficiency; The ASPNL module can capture ECG signal features from multiple scales to enhance the efficiency of feature extraction. Experimental evidence indicates that the ECG segmentation model, NGA-Net, introduced in this research, exhibits superior performance in comparison to other methodologies when tested on the publicly available LUDB dataset, which demonstrates the effectiveness of NGANet.In this research, we adopt a semi-supervised learning strategy for training the NGA-Net in scenarios with small sample sizes, leveraging data augmentation and consistency training methodologies. The experimental findings corroborate the effectiveness of semi-supervised learning in augmenting the performance of deep learning models.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 25","pages":"131711H - 131711H-6"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the continuous development of semiconductor technology, monolithic integration faces problems such as high design costs and long research period. The chiplet effectively improves the yield rate and shortens the research and development cycle by splitting a single die into multiple dies with different functions for advanced packaging integration. However, compared to monolithic integration, inter-die communication is limited by pin density and physical distance, and die interconnects bring higher latency. At the same time, each die has an independent structure, and accessing the same address space will cause system-level cache coherence issues. Therefore, we design a system-level cache based on the directory-based hybrid consistency protocol, and use optimization strategies such as shared bit and add interconnection channels between dies to improve the efficiency of inter-core coherence maintenance. We use GEM5 in conjunction with the SPLASH-2 benchmark to compare with an unoptimized directory-based hybrid coherence protocol. The results show that the program running speed is increased by 19.3%, the average memory access time is reduced by 23.3%, and the consistency protocol traffic is reduced by 37.8%.
{"title":"Design of an efficient hybrid cache coherence protocol on chiplet architecture","authors":"Ruqing Wang, Lixin Yu, Zhuang Wei","doi":"10.1117/12.3031958","DOIUrl":"https://doi.org/10.1117/12.3031958","url":null,"abstract":"With the continuous development of semiconductor technology, monolithic integration faces problems such as high design costs and long research period. The chiplet effectively improves the yield rate and shortens the research and development cycle by splitting a single die into multiple dies with different functions for advanced packaging integration. However, compared to monolithic integration, inter-die communication is limited by pin density and physical distance, and die interconnects bring higher latency. At the same time, each die has an independent structure, and accessing the same address space will cause system-level cache coherence issues. Therefore, we design a system-level cache based on the directory-based hybrid consistency protocol, and use optimization strategies such as shared bit and add interconnection channels between dies to improve the efficiency of inter-core coherence maintenance. We use GEM5 in conjunction with the SPLASH-2 benchmark to compare with an unoptimized directory-based hybrid coherence protocol. The results show that the program running speed is increased by 19.3%, the average memory access time is reduced by 23.3%, and the consistency protocol traffic is reduced by 37.8%.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":" 20","pages":"131711I - 131711I-8"},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141370001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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